Food image recognition using deep learning in climate change issue
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Updated
Sep 10, 2020 - Jupyter Notebook
Food image recognition using deep learning in climate change issue
This is an image classification project which was carried out during "Applied Machine Learning and Data Science" in Indian Institute of Technology, Kanpur
Pretrained ConvNets for pytorch: NASNet, ResNeXt, ResNet, InceptionV4, InceptionResnetV2, Xception, DPN, etc.
An end-to-end CNN Image Classification Model which identifies the bird in your image
CNN - object detection, classification & various model tuning for prediction optimization
A wrapper library over several open source cnn models for tensorflow -2.x.
A collection of deep learning models for rice classification using PyTorch, torchvision, and scikit-learn, with performance metrics evaluated using Slurm jobs.
End-to-end deep learning pipeline to classify images of dogs and humans to determine what breed the human or dog most resembles
Appolo's Ear is an ensemble of three music genre classification neural networks, a nginx server, and a demonstrative react frontend. Its backend is glued together with Docker and Docker compose.
Solutions to the Advanced CNN course by the Lazy Programmer and all CNN Models I've worked on
A collection of CNN models are trained on Cloud TPU by using PyTorch/XLA
This repo contains implementation of deep learning-based steel surface defect segmentation models. Extensive experiments on several deep learning frameworks have been presented with various performance analysis and comparison.
This research enhances early disease diagnosis by analyzing retinal blood vessels in fundus images using deep learning. It employs eight pre-trained CNN models and Explainable AI techniques.
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